MLECO-2235: Fix documentation

Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Change-Id: If8d6bf60cd4961be4c29f46ea75422b093185b04

5 files changed, 23 insertions, 23 deletions

diff --git a/docs/sections/building.md b/docs/sections/building.md
index 0d6361b..f0c7310 100644
--- a/docs/sections/building.md
+++ b/docs/sections/building.md
@@ -9,14 +9,14 @@
       - [Fetching resource files](#fetching-resource-files)
     - [Building for default configuration](#building-for-default-configuration)
     - [Create a build directory](#create-a-build-directory)
-    - [Configuring the build for MPS3 SSE-300](#configuring-the-build-for-mps3-sse-300)
+    - [Configuring the build for MPS3 SSE-300](#configuring-the-build-for-mps3-sse_300)
       - [Using GNU Arm Embedded toolchain](#using-gnu-arm-embedded-toolchain)
       - [Using Arm Compiler](#using-arm-compiler)
       - [Generating project for Arm Development Studio](#generating-project-for-arm-development-studio)
       - [Working with model debugger from Arm Fast Model Tools](#working-with-model-debugger-from-arm-fast-model-tools)
       - [Configuring with custom TPIP dependencies](#configuring-with-custom-tpip-dependencies)
-    - [Configuring native unit-test build](#configuring-native-unit-test-build)
-    - [Configuring the build for simple_platform](#configuring-the-build-for-simple_platform)
+    - [Configuring native unit-test build](#configuring-native-unit_test-build)
+    - [Configuring the build for simple-platform](#configuring-the-build-for-simple_platform)
     - [Building the configured project](#building-the-configured-project)
   - [Building timing adapter with custom options](#building-timing-adapter-with-custom-options)
   - [Add custom inputs](#add-custom-inputs)
@@ -211,7 +211,7 @@ The build process uses three major steps:
 2. Configure the build for the platform chosen. This stage includes:
     - CMake options configuration
     - When `<use_case>_MODEL_TFLITE_PATH` build options are not provided, the default neural network models can be
-      downloaded from [Arm ML-Zoo](https://github.com/ARM-software/ML-zoo/). For native builds, the network input and
+      downloaded from [Arm ML-Zoo](https://github.com/ARM-software/ML-zoo). For native builds, the network input and
       output data for tests are downloaded.
     - Some files such as neural network models, network inputs, and output labels are automatically converted into C/C++
       arrays, see: [Automatic file generation](#automatic-file-generation).
@@ -412,7 +412,7 @@ bin
 └── ethos-u-<usecase1>
 ```
 
-### Configuring the build for simple_platform
+### Configuring the build for simple-platform
 
 ```commandline
 cmake ../ -DTARGET_PLATFORM=simple_platform
@@ -549,13 +549,13 @@ For a clock rate of 500MHz, this would translate to:
 - With a read latency of 64 cycles, and maximum pending reads as 2, each read could be a maximum of 64 or 128 bytes. As
   defined for the *Ethos-U* NPU AXI bus attribute.
 
-    The bandwidth is calculated solely by read parameters:
+  The bandwidth is calculated solely by read parameters:
 
-    ![Bandwidth formula](../media/F3.png)
+  ![Bandwidth formula](../media/F3.png)
 
-    This is higher than the overall bandwidth dictated by the bus parameters of:
+  This is higher than the overall bandwidth dictated by the bus parameters of:
 
-    ![Overall bandwidth formula](../media/F4.png)
+  ![Overall bandwidth formula](../media/F4.png)
 
 This suggests that the read operation is only limited by the overall bus bandwidth.
 
@@ -647,8 +647,8 @@ After compiling, your custom model has now replaced the default one in the appli
 ## Optimize custom model with Vela compiler
 
 > **Note:** This tool is not available within this project. It is a Python tool available from
-> <https://pypi.org/project/ethos-u-vela/>.\
-The source code is hosted on <https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/>.
+> <https://pypi.org/project/ethos-u-vela/>.
+> The source code is hosted on <https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/>.
 
 The Vela compiler is a tool that can optimize a neural network model into a version that can run on an embedded system
 containing an *Ethos-U* NPU.
diff --git a/docs/sections/customizing.md b/docs/sections/customizing.md
index 4cea26f..3104986 100644
--- a/docs/sections/customizing.md
+++ b/docs/sections/customizing.md
@@ -7,7 +7,7 @@
   - [Application context](#application-context)
   - [Profiler](#profiler)
   - [NN Model API](#nn-model-api)
-  - [Adding custom ML use-case](#adding-custom-ml-use-case)
+  - [Adding custom ML use-case](#adding-custom-ml-use_case)
   - [Implementing main loop](#implementing-main-loop)
   - [Implementing custom NN model](#implementing-custom-nn-model)
     - [Define ModelPointer and ModelSize methods](#define-modelpointer-and-modelsize-methods)
@@ -15,7 +15,7 @@
   - [Printing to console](#printing-to-console)
   - [Reading user input from console](#reading-user-input-from-console)
   - [Output to MPS3 LCD](#output-to-mps3-lcd)
-  - [Building custom use-case](#building-custom-use-case)
+  - [Building custom use-case](#building-custom-use_case)
 
 This section describes how to implement a custom Machine Learning application running on Arm® *Corstone™-300* based FVP
 or on the Arm® MPS3 FPGA prototyping board.
@@ -441,7 +441,7 @@ These functions are wrappers around the functions generated in the C++ file cont
 array. This generation the C++ array from the `.tflite` file, logic needs to be defined in the `usecase.cmake` file for
 this `HelloWorld` example.
 
-For more details on `usecase.cmake`, refer to: [Building custom use-case](#building-custom-use-case).
+For more details on `usecase.cmake`, refer to: [Building options](./building.md#build-options).
 
 For details on code generation flow in general, refer to: [Automatic file generation](./building.md#automatic-file-generation).
 
@@ -641,7 +641,7 @@ twice:
 platform.data_psn->present_data_image((uint8_t *) inputTensor->data.data, 224, 224, 3, 10, 35, 2);
 ```
 
-Please refer to the [Hardware Abstraction Layer (HAL) API](#hardware-abstraction-layer-hal-api) section for more data presentation functions.
+Please refer to the [Hardware Abstraction Layer API](./customizing.md#hardware-abstraction-layer-api) section for more data presentation functions.
 
 ## Building custom use-case
 
diff --git a/docs/sections/deployment.md b/docs/sections/deployment.md
index 6c90c87..3e58464 100644
--- a/docs/sections/deployment.md
+++ b/docs/sections/deployment.md
@@ -2,10 +2,10 @@
 
 - [Deployment](#deployment)
   - [Fixed Virtual Platform](#fixed-virtual-platform)
-    - [Setting up the MPS3 Arm Corstone-300 FVP](#setting-up-the-mps3-arm-corstone-300-fvp)
+    - [Setting up the MPS3 Arm Corstone-300 FVP](#setting-up-the-mps3-arm-corstone_300-fvp)
     - [Deploying on an FVP emulating MPS3](#deploying-on-an-fvp-emulating-mps3)
   - [MPS3 board](#mps3-board)
-    - [MPS3 board top-view](#mps3-board-top-view)
+    - [MPS3 board top-view](#mps3-board-top_view)
     - [Deployment on MPS3 board](#deployment-on-mps3-board)
 
 The sample application for Arm® *Ethos™-U55* can be deployed on two target platforms:
diff --git a/docs/sections/memory_considerations.md b/docs/sections/memory_considerations.md
index a89175a..599c902 100644
--- a/docs/sections/memory_considerations.md
+++ b/docs/sections/memory_considerations.md
@@ -4,10 +4,10 @@
   - [Introduction](#introduction)
   - [Understanding memory usage from Vela output](#understanding-memory-usage-from-vela-output)
     - [Total SRAM used](#total-sram-used)
-    - [Total Off-chip Flash used](#total-off-chip-flash-used)
+    - [Total Off-chip Flash used](#total-off_chip-flash-used)
   - [Non-default configurations](#non-default-configurations)
   - [Tensor arena and neural network model memory placement](#tensor-arena-and-neural-network-model-memory-placement)
-  - [Memory usage for ML use-cases](#memory-usage-for-ml-use-cases)
+  - [Memory usage for ML use-cases](#memory-usage-for-ml-use_cases)
   - [Memory constraints](#memory-constraints)
 
 ## Introduction
@@ -16,7 +16,7 @@ This section provides useful details on how the Machine Learning use-cases of th
 
 Although the guidance provided here is concerning the Arm® *Corstone™-300* system, it is fairly generic and is
 applicable for other platforms too. The Arm® *Corstone™-300* is composed of both the Arm® *Cortex™-M55* and the Arm®
-*Ethos™-U* NPU. The memory map for the Arm® *Cortex™-M55* core can be found in the [Appendix](./appendix.md).
+*Ethos™-U* NPU. The memory map for the Arm® *Cortex™-M55* core can be found in the [Appendix](./appendix.md#appendix).
 
 The Arm® *Ethos™-U* NPU interacts with the system through two AXI interfaces. The first one, is envisaged to be the
 higher-bandwidth, lower-latency, interface. In a typical system, this is wired to an SRAM as it is required to service
@@ -75,7 +75,7 @@ For further information, please refer to: [vela.ini](../../scripts/vela/vela.ini
 To make use of a neural network model that is optimized for this configuration, the linker script for the target
 platform must be changed. By default, the linker scripts are set up to support the default configuration only.
 
-For script snippets, please refer to: [Memory constraints](#memory-constraints).
+For script snippets, please refer to: [Memory constraints](./memory_considerations.md#memory-constraints).
 
 > **Note:**
 >
@@ -130,7 +130,7 @@ Both the MPS3 Fixed Virtual Platform (FVP) and the MPS3 FPGA platform share the
 design. The CMake configuration parameter `TARGET_SUBSYSTEM` sets the design, which is described in:
 [build options](./building.md#build-options).
 
-The memory map exposed by this design is located in the [Appendix](./appendix.md), and can be used as a reference when
+The memory map exposed by this design is located in the [Appendix](./appendix.md#appendix), and can be used as a reference when
 editing the linker script. This is useful to make sure that the region boundaries are respected. The snippet from the
 scatter file is as follows:
 
diff --git a/docs/sections/testing_benchmarking.md b/docs/sections/testing_benchmarking.md
index d040d17..43f74c7 100644
--- a/docs/sections/testing_benchmarking.md
+++ b/docs/sections/testing_benchmarking.md
@@ -27,7 +27,7 @@ The folders contain the following information:
 - `use_case`: Every use-case specific test in their respective folders.
 - `utils`: Utility sources that are only used within the tests.
 
-When [configuring](./building.md#configuring-the-build-native-unit-test) and
+When [configuring](./building.md#configuring-native-unit_test-build) and
 [building](./building.md#building-the-configured-project) for your `native` target platform, the results of the build is
 placed under `<build folder>/bin/` folder. For example: